Two-Dimensional Beam Size Measurements with X-Ray Heterodyne Near Field Speckles
176
M. Siano, L. Teruzzi
Università degli Studi di Milano, Milano, Italy
D. Butti, A. Goetz, T. Lefèvre, S. Mazzoni, G. Trad
CERN, Meyrin, Switzerland
U. Iriso, A.A. Nosych, E. Solano, L. Torino
ALBA-CELLS Synchrotron, Cerdanyola del Vallès, Spain
B. Paroli, M.A.C. Potenza
Universita’ degli Studi di Milano & INFN, Milano, Italy
We report on 2D beam size measurements with a novel interferometric technique named Heterodyne Near Field Speckles, capable of resolving few-micrometer beam sizes. It relies on the interference between the weak spherical waves scattered by a colloidal suspension and the intense transilluminating X-ray beam. Fourier analysis of the resulting speckles enables full 2D coherence mapping of the incoming radiation, from which the beam sizes along the two orthogonal directions are retrieved. We show experimental results obtained with 12.4 keV X-rays at the NCD-SWEET undulator beamline at ALBA, where the vertical beam size has been changed between 5 and 15 micrometers by varying the beam coupling. The results agree well with the estimated beam sizes from the pinhole calculations. Finally, we discuss recent investigations on alternative targets aimed at improving the signal-to-noise ratio of the technique.
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Real-Time Beam Detection and Tracking From Pinhole Imaging System Based on Machine Learning
272
A.A. Nosych, U. Iriso
ALBA-CELLS Synchrotron, Cerdanyola del Vallès, Spain
At ALBA Synchrotron each of the two in-air pinhole imaging systems is able to see several beam spots at once due to specific pinhole grid with 3x3 holes placed in the path of the X-ray fan. Each beam image has its own properties, such as source pinhole aperture size, its Point Spread Function (PSF) and copper filter thickness, all of which impact the electron beam size calculation. Until now, these parameters were applied manually to the pinhole device servers for numerical image analysis, so this semi-manual beam size calculator is subject to frequent adjustments and human monitoring. This study looks at feasibility of training and pointing an Artificial Neural Network (ANN) at image stream coming from pinhole cameras in real time, track all detected beam spots and analyze them, with the end goal to automate the whole pinhole beam image processing.
